Sleep assessment using accelerometry: Not all algorithms are equal
Abstract
Abstract Study objectives Accelerometry devices are increasingly used to assess sleep. However, whether different algorithms provide consistent estimates remains uncertain. This study compared sleep parameters derived from two accelerometry‐based algorithms and a self‐reported sleep journal. Methods Data were obtained from the second (2014–2017; n = 2724; 53.3% women; 62.0 ± 10.0 years) and third (2018–2021; n = 2087; 53.5% women; 65.1 ± 9.6 years) follow‐ups of the CoLaus|PsyCoLaus study. Seven‐day accelerometry data were analysed using GGIR (R‐based) and MACRO (Excel‐based) algorithms. A subset of participants also completed an ecological momentary assessment (EMA) sleep diary. Sleep onset (
Fields of Study & Subjects
Sleep and related disorders
EEG and Brain-Computer Interfaces
Sleep and Work-Related Fatigue
Publication details
- Journal / source
- Sleep research.
- Volume
- 3
- Issue
- 1
- Pages
- 11–22
- Publication date
- 9 January 2026
- Language
- EN